CÓRDOBA NATIONAL UNIVERSITY
College of Agriculture, P.O. Box 509, 5000 Córdoba, Argentina.
Correlation of seed characteristics to grain yield in a population improvement program.
I. Argüello, R. Maich, and R.H. Rolando.
By detecting changes in the morphology of wheat seeds in a recurrent selection scheme, we hope to improve grain yield under semiarid environmental conditions of cultivation. From a random sample of 50 seeds per family, width, thickness, and length were measured. A similar sample was made for 1,000-kernel weight. After 2 years, significant differences between the mean family values corresponding to the C3 an C0 cycles of selection were observed for width and thickness, with reductions of 2.9 % and 2.7 %, respectively. The materials harvested in 1996 showed significantly higher values for all three morphological traits analyzed than those from 1997, which was a drier year. Differences in seed length were the greatest (5.1 %). Thousand-kernel weight decreased 11.5 % by the end of the third cycle of recurrent selection. On the other hand, nonsignificant differences between the mean values of each year were observed. More cycles of selection and reselection within each population are needed to confirm the negatively correlated responses.
Water deficit effects on the flag leaf characters related to a microevolutionary process.
S.P. Gil, M.M. Cerana, and R.H. Maich.
Changes other than what the breeder wants can happen in a plant
breeding program. Modifications associated with the main characteristics
can occur, and others may be related to enviromental conditions.
We worked with two groups of bread wheat, with different microevolutionary
degrees, obtained from a recurrent selection scheme and sown in
an experimental field during 2 consecutive years (1995 was drier
than 1996). The field was at Ferreyra (Córdoba, Argentina),
at 31°29' S and 64°00' W. We analyzed 11 families from
each cycle, from C0 (initial) to C3 (more evolved). We compared
and analyzed the following flag leaf characteristics:
morphological - length, width, and area and
epidermal: - long cell frequency,
silico-suberose pair frequency,
stomatal frequency,
prickle frequency,
length of stomatal complex, and
width of stomatal complex.
The results showed significant differences between years for the three morphological characters (their values were lower in 1995), and the epidermical variables long cell frequency, silico-suberose pairs frequency, and length and width of the stomatal complex. Between cycles, we found significant changes only in the flag leaf width (p < 0.05) and stomatal frequency (p < 0.1). In both instances C3 families showed higher mean values than C0 families.
Wheat bread-making quality after three cycles recurrent selection for grain yield.
M.E. Dubois, Z.A. Gaido, G.A. Manera, and R.H. Maich.
We evaluated three cycles of recurrent selection for grain yield in bread wheat and its effects on several quality parameters. Twelve S1-derived families from each of the analyzed cycles (C0, C1,C2, and C3) were evaluated for grain yield during 2 consecutive years (Maich RH, Ann Wheat Newslet 44:34). For bread-making quality, any measured trait did not show significant differences between cycles. A similar result was observed in a 3-year trial, where two cycles of recurrent selection were evaluated (Gaido et al., Ann Wheat Newslet 44:34). Protein and gluten percentages during 1997 were lower than those of 1996. Moreover, those flour samples with low protein percentages failed during the agglutination process. These mean protein differences between years are due to constrasting environmental conditions. A similar tendency was observed for the check varieties. Though nonsignificant differences between cycles were observed for rate of dough development time, in general, they were excessively long, probably because of the low percentage of flour protein in 1997. The mixograph analysis showed that the 73 % of the families were included in classes 6 and 7. However, some C3 families were of classes 9 and 10. We concluded that after three cycles of recurrent selection for grain yield, significant direct genetic progress was made without any significant effects on the bread-making quality traits measured.
Publications.
Cerana MM, Gil SP, and Maich RH. 1998. Espigas de trigo (Triticum aestivum L.) en relación al número de flores en un programa de selección recurrente. In: Proc IV Cong Nat Trigo, II Symp Nat Cereales de Siembra Otoño Invernal. Mar Del Plata. 1:9-10.
Salvagiotti F and Maich R. 1998. Recurrent selection for grain yield in wheat (Titicum aestivum L.). J Genet Breed 58 (In press).
Maich RH, Gil SP, Arguello I, Rolando R, Dubois ME, and Cerana MM. 1998. Microevolution in bread wheat. Effects on some biological aspects related to grain yield. In: Proc 9th Inter Wheat Genet Symp (Slinkard AE ed). University Extension Press, Saskatoon, Saskatchewan, Canada. 2:86-88.
Maich RH, Gaido ZA, Gil SP, and Dubois ME. 1998. Desarrollo de tres ciclos de selección recurrente en trigo pan (Triticum aestivum L.) con crecientes rendimientos potenciales en semilla. Su efecto sobre la calidad panadera. In: Proc IV Cong Nat Trigo, II Symp Nat Cereales de Siembra Otoño-Invernal. Mar Del Plata. 1:14-15.
INSTITUTE OF BIOLOGICAL RESOURCES - INTA
Institute of Climate and Water - INTA - CIRN.
CC 25, (1712) Castelar, Buenos Aires, Argentina.
Prediction of wheat stem rust severity using a resistance index and meteorological variables.
Ricardo C. Moschini and Beatríz A. Pérez.
Wheat stem rust epidemics were analyzed for growing seasons from 1972 to 1989. Stem rust severity values recorded at Paraná Experimental Station (31 50 S, 60 31 W) were used to identify the best genetic and environmental predictors of disease severity. Stem rust severity (early planting date) could be predicted (R2 = 0.88) as a function of a resistance index, heat accumulation, relative humidity, and precipitation.
The mean percent observed severities were calculated from the maximum stem rust cultivar assessments observed at the Paraná National Nurseries (ROET). The information on cultivar disease resistance was derived from ETRE multilocation field tests made under high inoculum levels. The proposed models for predicting stem rust severities were validated using 199098 rust severity data from Paraná. Daily meteorological data recorded at the Paraná weather station were analyzed using SAS procedures (release 6.03, SAS Institute Inc., Cary, NC). In several monitoring periods, environmental variables were calculated and then evaluated for their utility in predicting stem rust. Several starting dates and lengths, expressed as accumulated degree days, were tested from late July to early October using the R2 SAS procedure to identify the most appropriate monitoring period. Linear regression models were used to examine the associations of genetic and meteorological factors with mean observed severity. Equations with up to three independent variables were developed using the reg SAS procedure. The final selection of the best regression equations was based on the determination coefficients (R2). The monitoring period started on 20 August (Julian day 232) and ended when 780 degree days were accumulated and showed the closest climate-disease relationships.
The best simple and multiple equations for predicting mean maximum stem rust severity, including meteorological and genetic factors as linear independent components, were y = -7.5012 + 1.4166 DRHPR (R2 = 0.80), y = -67.7711 + 0.1519 DD7 + 1.3934 DRHPR (R2 = 0.85), and y = -63.9125 + 0.1507 DD7 - 9.5164 RI + 1.445 DRHPR (R2 = 0.88), where RI was the resistance index ranging from 0 (resistant cultivar) to 1 (susceptible cultivar), DD7 represented the heat accumulation with base mean daily temperatures of 7 C, and DRHPR was obtained by adding the days with precipitations and/or days with minimum temperatures higher than 8 C and air relative humidity higher than 81 %. A close agreement was recorded between observed and predicted disease severity levels at Paraná between 1990-97.
Publications.
Moschini RC and Fortugno C. 1996. Predicting wheat head blight incidence using models based on meteorological factors in Pergamino, Argentina. Eur J Plant Pathol 102:211-218.
Moschini RC and Pérez BA. 1999. Predicting wheat leaf rust severity using planting date, genetic resistance, and weather variables. Plant Dis 83:381-384.
RodríguEZ Amieva PJ, Mujica FL, Frecha JH, and Antonelli
EF. 1972-1984. Ensayo territorial de resistencia a enfermedades
en trigo, triticale, avena, cebada, centeno y lino en la región
cerealera Argentina boletines informativos. Departamento de Genética.
INTA, Castelar, Argentina.